This study has adopted theoretical frameworks of social capital, social networks and the Community of Practice to study how different types of relationships influence the knowledge sharing relationship. This paper aims to suggest that building social capital, particularly structural capital, is part of expected key in knowledge sharing networks.
Using social capital theory, through social network analysis of 111 management students in the US business school, identified key social capital dimension in knowledge sharing networks. To incorporate the interdependency among examined relationships, network logistic regression with the quadric assignment procedure was used.
The proposed research model showed that about 98% of the existence of knowledge sharing relationship could be correctly predicted. Among three dimensions of social capital, this study found a superior influence of the structural dimension (i.e. task interdependence) in predicting having a knowledge sharing relationship. The significant effect of trust and friendship network on knowledge sharing was also found. Implications for practice and suggestions for future research were also discussed.
Existing literature as to how people learn through knowledge sharing is limited in at least two important ways. First, scholars of knowledge management acknowledge that organizational knowledge originates from dyadic relationships between or among individuals at work. However, prior research has heavily relied on survey responses from one’s perception of knowledge sharing experience, viewing as unidirectional. Second, substantial attention of prior research has been devoted to the factors of individual attributes. Emphasizing individual interactions as the fundamental building blocks of learning, this study focuses more on relational characteristics of knowledge sharing based on social capital theory.
Han, S.H., Yoon, S.W. and Chae, C. (2020), "Building social capital and learning relationships through knowledge sharing: a social network approach of management students’ cases", Journal of Knowledge Management, Vol. 24 No. 4, pp. 921-939. https://doi.org/10.1108/JKM-11-2019-0641
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